GPT-6 guide: a build checklist for long-running agents, and what's still unsolved

GPT-6 指南读下来：long-horizon agent 的实现清单，和它们没说的部分

A reading of the GPT-6 guide lays out how to build long-running agents, shifting the focus from homegrown memory management to collaboration and authorization while a task runs. Drawing on OpenAI documentation, it covers compaction and persistent reasoning, mid-turn steering, asynchronous tool calls and multi-agent delegation, plus steps for model choice, caching, skill rules and human approval. It also flags limits: correction instructions lost on disconnect, mutually exclusive API parameters, and encrypted compaction that is hard to audit.

Why it matters: It splits long-task engineering into managed memory and collaboration control, and assigns clear roles to async execution, mid-run correction and human approval.